The Experiment Data Depot: A Web-Based Software Tool for Biological Experimental Data Storage, Sharing, and Visualization
Abstract
Although recent advances in synthetic biology allow us to produce biological designs more efficiently than ever, our ability to predict the end result of these designs is still nascent. Predictive models require large amounts of high-quality data to be parametrized and tested, which are not generally available. Here, we present the Experiment Data Depot (EDD), an online tool designed as a repository of experimental data and metadata. EDD provides a convenient way to upload a variety of data types, visualize these data, and export them in a standardized fashion for use with predictive algorithms. In this paper, we describe EDD and showcase its utility for three different use cases: storage of characterized synthetic biology parts, leveraging proteomics data to improve biofuel yield, and the use of extracellular metabolite concentrations to predict intracellular metabolic fluxes.
- Authors:
-
- DOE Joint BioEnergy Institute, Emeryville, California 94608, United States, Biotechnology and Bioengineering and Biomass Science and Conversion Department, Sandia National Laboratories, Livermore, California 94550, United States
- DOE Joint BioEnergy Institute, Emeryville, California 94608, United States, DOE Agile BioFoundry, Emeryville, California 94608, United States, Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
- DOE Joint BioEnergy Institute, Emeryville, California 94608, United States, Biotechnology and Bioengineering and Biomass Science and Conversion Department, Sandia National Laboratories, Livermore, California 94550, United States, DOE Agile BioFoundry, Emeryville, California 94608, United States
- DOE Joint BioEnergy Institute, Emeryville, California 94608, United States
- DOE Joint BioEnergy Institute, Emeryville, California 94608, United States, Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
- DOE Joint BioEnergy Institute, Emeryville, California 94608, United States, DOE Agile BioFoundry, Emeryville, California 94608, United States, Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States, Department of Chemical and Biomolecular Engineering, University of California, Berkeley, California 94720, United States, Department of Bioengineering, University of California, Berkeley, California 94720, United States
- DOE Joint BioEnergy Institute, Emeryville, California 94608, United States, DOE Agile BioFoundry, Emeryville, California 94608, United States, Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
- DOE Joint BioEnergy Institute, Emeryville, California 94608, United States, DOE Agile BioFoundry, Emeryville, California 94608, United States, Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States, DNA Synthesis Science Program, DOE Joint Genome Institute, Walnut Creek, California 94598, United States
- DOE Joint BioEnergy Institute, Emeryville, California 94608, United States, DOE Agile BioFoundry, Emeryville, California 94608, United States, Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States, BCAM, Basque Center for Applied Mathematics, 48009 Bilbao, Spain
- Publication Date:
- Research Org.:
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
- Sponsoring Org.:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE)
- OSTI Identifier:
- 1400002
- Alternate Identifier(s):
- OSTI ID: 1436657; OSTI ID: 1507547
- Grant/Contract Number:
- AC02-05CH11231
- Resource Type:
- Published Article
- Journal Name:
- ACS Synthetic Biology
- Additional Journal Information:
- Journal Name: ACS Synthetic Biology Journal Volume: 6 Journal Issue: 12; Journal ID: ISSN 2161-5063
- Publisher:
- American Chemical Society
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 96 KNOWLEDGE MANAGEMENT AND PRESERVATION; -omics data; data mining; data standards; database; flux analysis; synthetic biology
Citation Formats
Morrell, William C., Birkel, Garrett W., Forrer, Mark, Lopez, Teresa, Backman, Tyler W. H., Dussault, Michael, Petzold, Christopher J., Baidoo, Edward E. K., Costello, Zak, Ando, David, Alonso-Gutierrez, Jorge, George, Kevin W., Mukhopadhyay, Aindrila, Vaino, Ian, Keasling, Jay D., Adams, Paul D., Hillson, Nathan J., and Garcia Martin, Hector. The Experiment Data Depot: A Web-Based Software Tool for Biological Experimental Data Storage, Sharing, and Visualization. United States: N. p., 2017.
Web. doi:10.1021/acssynbio.7b00204.
Morrell, William C., Birkel, Garrett W., Forrer, Mark, Lopez, Teresa, Backman, Tyler W. H., Dussault, Michael, Petzold, Christopher J., Baidoo, Edward E. K., Costello, Zak, Ando, David, Alonso-Gutierrez, Jorge, George, Kevin W., Mukhopadhyay, Aindrila, Vaino, Ian, Keasling, Jay D., Adams, Paul D., Hillson, Nathan J., & Garcia Martin, Hector. The Experiment Data Depot: A Web-Based Software Tool for Biological Experimental Data Storage, Sharing, and Visualization. United States. https://doi.org/10.1021/acssynbio.7b00204
Morrell, William C., Birkel, Garrett W., Forrer, Mark, Lopez, Teresa, Backman, Tyler W. H., Dussault, Michael, Petzold, Christopher J., Baidoo, Edward E. K., Costello, Zak, Ando, David, Alonso-Gutierrez, Jorge, George, Kevin W., Mukhopadhyay, Aindrila, Vaino, Ian, Keasling, Jay D., Adams, Paul D., Hillson, Nathan J., and Garcia Martin, Hector. Fri .
"The Experiment Data Depot: A Web-Based Software Tool for Biological Experimental Data Storage, Sharing, and Visualization". United States. https://doi.org/10.1021/acssynbio.7b00204.
@article{osti_1400002,
title = {The Experiment Data Depot: A Web-Based Software Tool for Biological Experimental Data Storage, Sharing, and Visualization},
author = {Morrell, William C. and Birkel, Garrett W. and Forrer, Mark and Lopez, Teresa and Backman, Tyler W. H. and Dussault, Michael and Petzold, Christopher J. and Baidoo, Edward E. K. and Costello, Zak and Ando, David and Alonso-Gutierrez, Jorge and George, Kevin W. and Mukhopadhyay, Aindrila and Vaino, Ian and Keasling, Jay D. and Adams, Paul D. and Hillson, Nathan J. and Garcia Martin, Hector},
abstractNote = {Although recent advances in synthetic biology allow us to produce biological designs more efficiently than ever, our ability to predict the end result of these designs is still nascent. Predictive models require large amounts of high-quality data to be parametrized and tested, which are not generally available. Here, we present the Experiment Data Depot (EDD), an online tool designed as a repository of experimental data and metadata. EDD provides a convenient way to upload a variety of data types, visualize these data, and export them in a standardized fashion for use with predictive algorithms. In this paper, we describe EDD and showcase its utility for three different use cases: storage of characterized synthetic biology parts, leveraging proteomics data to improve biofuel yield, and the use of extracellular metabolite concentrations to predict intracellular metabolic fluxes.},
doi = {10.1021/acssynbio.7b00204},
journal = {ACS Synthetic Biology},
number = 12,
volume = 6,
place = {United States},
year = {Fri Sep 08 00:00:00 EDT 2017},
month = {Fri Sep 08 00:00:00 EDT 2017}
}
https://doi.org/10.1021/acssynbio.7b00204
Web of Science
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